Movie listings

Movie listings

How to pick a movie? It's Friday night, movie night. Or maybe you go on Saturday. Or maybe you want to rent or stream. What to see? (If you're looking for a classic, you ought to check out my movie site: www.asharperfocus.com.)

But you probably consult instead the reviewers in the newspaper or the magazines. You find that David Denby likes it and A. O. Scott doesn't, that Manohla Dargis thinks its so-so, and J. Hoberman thinks it's a masterpiece. So where does that leave you? Nowhere.

How about a collection of reviewers? The kind of thing you get from Rotten Tomatoes or metacritic. That's probably better, I think, than any one reviewer, unless you think you agree 100% with some reviewer. But reviewers are a special, doubtful lot who see altogether too many movies. Roger Ebert estimated that he sees ten a week. That seems to me to skew your judgment. Anything that is novel enough not to bore you is likely to please. And other things bias your verdicts like trying to keep in good with the industry, blowing your own horn, or arguing with other reviewers.


IMDb User Rating

IMDB User Rating

 

 

 

 

 

Here's how to pick a movie. You go to IMDb.com and you look up your potential title. Or you go IMDb.com > Movies > Showtimes & Tickets and ask IMDb to sort the movies in your neighborhood by "User Ratings." Either way, you'll get whether thousands of people liked the movie or not. Something like the image above with information like this:

         Midnight in Paris (2011)
         8.1/10 (8,319 votes)

         Mr. Popper's Penguins (2011)
         5.8/10 (2,629 votes)

Check your movie's User Rating. If it's over 8.0 go. Chances are you'll like it. That's a good pick. If it's under 7.0--bummer. In beween, check the synopsis, and you're on your own. Or you can play the same game on Rotten Tomatoes or metacritic.com with ordinary viewers, not reviewers. Don't use IMDb's MOVIEmeter. That tells you, IMDb says, "what people are interested in," not whether they liked the show. Get the User Ratings.


Bell-shaped curve

The Bell-shaped Curve

Why does this work? It's just the old bell-shaped curve. I assume, and I know this is a big assumption, that those viewers' verdicts form a standard bell-shaped Gaussian curve, neither bimodal, leptokurtic, nor platykurtic . It's too bad that IMDb doesn't give us the actual picture, but I would guess that it's fairly conventional, that most of the judgments fall between 5 and 9. Only the real lemons fall below 5.0.

If so, chances are 7 out of 10 that any given person's rating will fall within, say, one point of the median. (Again, I'm assuming, this time, a standard deviation of 1.) There's no guarantee, of course, but if you decide to go to a movie rated 8.1 (like Midnight in Paris, above), I think chances are 7 out of 10 that you'll rate it between either 7.1 and 9.1. In other words, chances are 7 out of 10 that you'll either really, really like the movie or you'll like it somewhat. Either way, you've won. And you have a 50-50 chance that you will like the movie more than the IMDb average.

Are we talking the wisdom of crowds here? James Surowiecki's well-known title? Not exactly. The argument that a group makes better decisions than an expert does about, say, stock picks or decisions about military intelligence applies to situations where there is a better and a worse or a right and a wrong. You either make money with your stock pick or you don't. The collective judgment on intelligence about terrorists is good or bad. But enjoying or not enjoying a morie--that's purely subjective. The question the crowd is answering isn't, Is this a good movie. It's, Did I enjoy this movie?

How about computers like Netflix's that pick what you'll like on the basis of what you liked before?

Netflix's computers have decided that I like "Mind-bending Suspenseful Independent Movies" and "French-Language Crime Thrillers." I'm not sure how Netflix arrived at that conclusion. My "recently watched" included Woody Allen's Bananas (1971) . Nevertheless that choice (and my rating) led Netflix's computers to recommend Allen's Crimes and Misdemeanors (1989) and Shadows and Fog (1992), altogether different from Bananas. Who knows how these computers' minds work? One thing for sure, though, they don't work the same way mine does.

But those 8,319 people who liked Midnight in Paris, their minds do work like mine or yours. Trust them.

 

About the Author

Norman Holland

Norman Holland, Ph.D., specializes in the psychology of the arts. His latest book is Literature and the Brain.

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